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000726291 020__ $$a9788132222538$$qelectronic book
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000726291 0247_ $$a10.1007/978-81-322-2253-8$$2doi
000726291 035__ $$aSP(OCoLC)ocn905854123
000726291 035__ $$aSP(OCoLC)905854123
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000726291 24500 $$aBenchmarking for performance evaluation$$h[electronic resource] :$$ba production frontier approach /$$cSubhash C. Ray, Subal C. Kumbhakar, Pami Dua, editors.
000726291 264_1 $$aNew Delhi :$$bSpringer,$$c2015.
000726291 300__ $$a1 online resource.
000726291 336__ $$atext$$btxt$$2rdacontent
000726291 337__ $$acomputer$$bc$$2rdamedia
000726291 338__ $$aonline resource$$bcr$$2rdacarrier
000726291 504__ $$aIncludes bibliographical references.
000726291 5050_ $$aIntroduction ? Ray, Subhash; Kumbhakar, Subal & Dua, Pami -- Chapter 1. Estimation of Technical Inefficiency in Production Frontier Models Using Cross-Sectional Data by Kumbhakar, Subal C. & Wang, Hung-Jen -- Chapter 2. Data Envelopment Analysis for Performance Evaluation: A Child?s Guide by Ray, Subhash C. & Chen, Lei -- Chapter 3. An Introduction to CNLS and StoNED Methods for Efficiency Analysis: Economic Insights and Computational Aspects by Johnson, Andrew L. and Kuosmanen, Timo -- Chapter 4. Dynamic Efficiency Measurement by Førsund, Finn R -- Chapter 5. Efficiency Measures for Industrial Organization by Ten Raa, Thijs -- Chapter 6. Multiplicative and Additive Distance Functions: Efficiency Measures and Duality by Pastor, Jesus T. & Aparicio, Juan.
000726291 506__ $$aAccess limited to authorized users.
000726291 520__ $$aThis book provides a detailed introduction to the theoretical and methodological foundations of production efficiency analysis using benchmarking. Two of the more popular methods of efficiency evaluation are Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA), both of which are based on the concept of a production possibility set and its frontier. Depending on the assumed objectives of the decision-making unit, a Production, Cost, or Profit Frontier is constructed from observed data on input and output quantities and prices. While SFA uses different maximum likelihood estimation techniques to estimate a parametric frontier, DEA relies on mathematical programming to create a nonparametric frontier. Yet another alternative is the Convex Nonparametric Frontier, which is based on the assumed convexity of the production possibility set and creates a piecewise linear frontier consisting of a number of tangent hyper planes. Three of the papers in this volume provide a detailed and relatively easy to follow exposition of the underlying theory from neoclassical production economics and offer step-by-step instructions on the appropriate model to apply in different contexts and how to implement them. Of particular appeal are the instructions on (i) how to write the codes for different SFA models on STATA, (ii) how to write a VBA Macro for repetitive solution of the DEA problem for each production unit on Excel Solver, and (iii) how to write the codes for the Nonparametric Convex Frontier estimation. The three other papers in the volume are primarily theoretical and will be of interest to PhD students and researchers hoping to make methodological and conceptual contributions to the field of nonparametric efficiency analysis.
000726291 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed April 1, 2015).
000726291 650_0 $$aBenchmarking (Management)
000726291 650_0 $$aProduction management.
000726291 7001_ $$aRay, Subhash C.,$$eeditor.
000726291 7001_ $$aKumbhakar, Subal,$$eeditor.
000726291 7001_ $$aDua, Pami,$$eeditor.
000726291 77608 $$iPrint version:$$z9788132222521
000726291 852__ $$bebk
000726291 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-81-322-2253-8$$zOnline Access$$91397441.1
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000726291 983__ $$aOnline
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